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The Cohort Effect: Insights and Explanations

Published online by Cambridge University Press:  10 June 2011

R. C. Willets
Affiliation:
Willets Consulting, 1 Crealock Grove, Woodford Green, Essex IG8 9QZ, U.K., Tel: +44(0)2085059006, Email: [email protected]

Abstract

The purpose of the report is to achieve a greater understanding of the United Kingdom ‘cohort effect’ by exploring research in other fields and analysing population mortality data by cause of death in more detail. The ‘cohort effect’ in this context is the observed phenomenon that people born in the U.K. between 1925 and 1945 (centred on the generation born in 1931) have experienced more rapid improvement in mortality than generations born either side of this period.

In a Continuous Mortality Investigation (CMI) Bureau working paper published in 2002, a similar trend was noted in the mortality experience of male pensioners and males with life assurance policies. The CMI Bureau investigation showed peak rates of improvement for the cohort born in 1926. Interim projection bases for future mortality experience were produced as a result of the study. The projections made various assumptions about the extent to which the observed cohort effect would continue to shape the pattern of future mortality improvement.

This report suggests that it is highly likely that the cohort effect has been caused by a number of different factors in combination. Prevalence of smoking from one generation to the next has certainly been one such factor. Furthermore, an analysis of patterns of cigarette smoking suggests that there is a degree of inevitability in some element of likely future improvement, especially for mortality at older ages from conditions strongly linked to smoking.

However, trends in heart disease and breast cancer mortality suggest that smoking is not the only factor. The differences between lung cancer and heart disease trends by year of birth are especially interesting. The report shows that there are two ‘sub-cohorts’ of the 1925 to 1945 cohort: an earlier group where the improvements may be largely due to smoking; and a later one where other factors, such as diet in early life, may have played a greater role.

Historic patterns of smoking behaviour by socio-economic class provide an explanation for the five-year difference in the year of birth showing the fastest improvements, i.e. the difference between 1926 for the CMI Bureau investigation and 1931 for the general population. It is also notable that the second ‘sub-cohort’ of high improvement, applying to people born in the early 1940s, can be seen in both population and CMI experience.

A case study examining Japanese mortality experience shows that strong cohort trends can be projected well into old age. This does not provide proof that the U.K. cohort effect will do the same. However, it does counter arguments that year of birth effects will inevitably wear off with age. It is especially interesting given recent epidemiological research linking early life experience with markers of ageing.

There are a number of reasons to believe that the U.K. cohort effect will have an enduring impact on rates of mortality improvement in future decades. These include historical patterns of smoking behaviour and the impact of early life experience on health in later life. There appears to be little evidence to support the idea that the width of the generation experiencing rapid improvement will reduce with time.

Type
Sessional meetings: papers and abstracts of discussions
Copyright
Copyright © Institute and Faculty of Actuaries 2004

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References

Barker, D.J.P., Osmond, C. & Law, C.M. (1989). The intrauterine and early postnatal origins of cardiovascular disease and chronic bronchitis. Journal of Epidemiology and Community Health, 43, 237240.Google Scholar
Barker, D.J.P. (1990). The fetal and infant origins of adult disease. British Medical Journal, 301, 1111.Google Scholar
Barker, D.J.P. (1995). The fetal origins of coronary heart disease. British Medical Journal, 311, 171174.CrossRefGoogle ScholarPubMed
Barker, D.J.P. & Lackland, D.T. (2002). Prenatal influences on stroke mortality in England & Wales. Stroke, 34(7), 16021603.Google Scholar
Caselli, G. (1996). Future longevity among the elderly. In Health and mortality among elderly populations. Edited by Caselli, Graziella and Lopez, Alan D.. Clarendon Press, Oxford.CrossRefGoogle Scholar
Continuous Mortality Investigation Mortality Sub-Committee (2002). Working paper 1: An interim basis for adjusting the ‘92 series’ mortality projections for cohort effects. CMIB, London.Google Scholar
Department of Health (1999). Saving lives: our healthier nation. H.M.S.O., London.Google Scholar
Derrick, V.P.A. (1927). Observations on (1) errors in age on the population statistics of England & Wales and (2) the changes in mortality indicated by the national records. Journal of the Institute of Actuaries, 58, 117159.CrossRefGoogle Scholar
Doll, R., Peto, R., Wheatley, K., Gray, R. & Sutherland, I. (1994). Mortality in relation to smoking: 40 years’ observations on male British doctors. British Medical Journal, 309, 901911.CrossRefGoogle ScholarPubMed
Eriksson, J.G., Forsen, T., Tuomilehto, J., Osmond, C. & Barker, D.J.P. (2001). Early growth and coronary heart disease in later life: longitudinal study. British Medical Journal, 322, 949953.Google Scholar
Evandrou, E. (1997). Baby boomers: ageing in the 21st century. Age Concern England, London.Google Scholar
Evandrou, E. & Falkingham, J. (2000). Looking back to look forward: lessons from four birth cohorts for ageing in the 21st century. Population Trends, 99, 2736.Google Scholar
Evandrou, E. & Falkingham, J. (2002). Smoking behaviour and socio-economic class: a cohort analysis, 1974 to 1998. Health Statistics Quarterly, 14, 3038.Google Scholar
Fogel, R.W. (1994). Economic growth, population theory, and physiology: the bearing of long-term processes on the making of economic policy. American Economic Review, 84(3), 369395.Google Scholar
Gavrilov, L.A. & Gavrilova, N. S. (1999). Season of birth and human longevity. Journal of Anti-Aging Medicine, 2(4), 365366.Google Scholar
Government Actuary's Department (1995). National population projections 1992-based. H.M.S.O., London.Google Scholar
Government Actuary's Department (2001). National population projections: review of methodology for projecting mortality. Government Actuary's Department, London.Google Scholar
Government Actuary's Department (2002). National population projections 2000-based. H.M.S.O., London.Google Scholar
Himes, C.L., Preston, S.H. & Condran, G.A. (1994). A relational model of mortality at older ages in low mortality countries. Population Studies, 48, 269291.Google Scholar
Human Mortality Database (2003). www.mortality.orgGoogle Scholar
Kermack, W.O., McKendrick, A.G. & McKinley, P.L. (1934). Death rates in Great Britain and Sweden: some general regularities and their significance. Lancet, 226, 698703.Google Scholar
Kuh, D. & Davey Smith, J. (1993). When is mortality risk determined? Historical insights into a current debate. Journal of the Society for the Social History of Medicine.CrossRefGoogle Scholar
Kuh, D., dos Santos Silva, I. & Barrett-Connor, E. (2002). Disease trends in women living in established market economies: evidence of cohort effects during the epidemiological The Cohort Effect: Insights and Explanations 877 transition. In A life course approach to women's health. Edited by Kuh, Diana and Hardy, Rebecca. Oxford University Press.Google Scholar
Lee, P.N. (2000). A review of the epidemiology of lung cancer related to active smoking. www.pnlee.co.ukGoogle Scholar
Lee, P.N. (2001). A review of the epidemiology of heart disease related to active smoking. www.pnlee.co.ukGoogle Scholar
Lee, P.N., Fry, J.S. & Forey, B.A. (1990). Trends in lung cancer, chronic obstructive lung disease, and emphysema death rates for England and Wales, 1941 - 85, and their relation to trends in cigarette smoking. Thorax, 45, 657665.Google Scholar
Lung & Asthma Information Agency (1993). Trends in lung cancer and mortality. Factsheet 93/1.Google Scholar
MacMinn, R. (2003). International mortality comparisons. Presentation to the Society of Actuaries, Vancouver. www.journalofriskandinsurance.orgGoogle Scholar
Mcpherson, K., Steel, C.M. & Dixon, J.M. (2000). Breast cancer - epidemiology, risk factors, and genetics. British Medical Journal, 321, 624628.CrossRefGoogle ScholarPubMed
Office of National Statistics (1997). The health of adult Britain 1841-1994. H.M.S.O., London.Google Scholar
Office of National Statistics (2001). Twentieth century mortality — CD with updates to 2000. H.M.S.O., London.Google Scholar
Office of National Statistics (2002a). Living in Britain: results from the 2001 General Household Survey. H.M.S.O., London.Google Scholar
Office of National Statistics (2002b). Mortality statistics Series DH2 no. 28. H.M.S.O., London.Google Scholar
Prynne, C.J., Paul, A.A., Price, G.M., Day, K.C., Hilder, W.S. & Wadsworth, M.E. (1999). Food and nutrient intake of a national sample of 4-year-old children in 1950: comparison with the 1990s. Public Health Nutrition, 2(4), 537547.CrossRefGoogle ScholarPubMed
Sayer, A.A., Cooper, C., Evans, J.R., Rauf, A., Wormald, R.P., Osmond, C. & Barker, D.J.P. (1998). Are rates of ageing determined in utero? Age Ageing, 27(5), 579583.Google Scholar
Tabeau, E. (2001). A review of demographic forecasting models for mortality. In Forecasting mortality in developed countries. Edited by Tabeau, Ewa, Jeths, Anneke van den Berg and Heathcote, Christopher. Kluwer Academic Publishers.CrossRefGoogle Scholar
Tuljapurkar, S. & Boe, C. (1998). Mortality change and forecasting: how much and how little do we know? North American Actuarial Journal, 2(4), 1347.CrossRefGoogle Scholar
Wadsworth, M.E.J., Cripps, H.A., Midwinter, R.A. & Colley, J.R.T. (1985). Blood pressure at age 36 years and social and familial factors, cigarette smoking and body mass in a national birth cohort. British Medical Journal, 291, 15341538.Google Scholar
Wadsworth, M.E.J. (1991). The imprint of time: childhood, history & adult life. Clarendon Press, Oxford.Google Scholar
Willets, R. (1999). Mortality in the next millennium. Paper presented to the Staple Inn Actuarial Society.Google Scholar
Wilmoth, J.R. (1997). In search of limits. In Between Zeus and the salmon: the biodemography of longevity. Edited by Wachter, Kenneth & Finch, Caleb. National Academy Press. Washington, D.C.Google Scholar
Wilmoth, J.R. (1990). Variation in vital rates by age, period & cohort. Sociological Methodology, 20, 295335.Google Scholar